Cohort explorer for visualizing comprehensive sample relationships through multi-modal feature variations

Abstract

A data-driven integrative visualization system and a method for visualization and exploration of the multi-modal features of a cohort of samples, is disclosed Specifically, a method for providing an interactive computation and visualization front-end of a genomics platform for presenting the complex multiparametric and high dimensional, multi-omic data of a patient with respect to a cohort of samples, that assists the user in understanding the similarities and differences across individual or groups of samples, identify correlation among different features and improve treatment planning and long term patient care, is described. The method may include obtaining and inputting multi-omic data of a patient and/or cohorts, identifying multi-modal feature variations and their relationships, and displaying this information in an interactive circular format on a GUI, from which the user can access further information. The system may provide an improved process of integrative analysis on a patient's multi-omic data for effective treatment planning.

What is claimed: 
     
         1 . A computer-implemented method for visualization and exploration of multi-modal features of a cohort of patient samples, the method comprising:
 generating a patient inter-relationship plot based upon at least two patient inter-relationship values;   displaying the patient inter-relationship plot on a graphical user interface;   wherein the patient inter-relationship plot comprises a plot of patient inter-relationship values for each patient, with each of the patient inter-relationship values represented by a patient icon;   a perimeter of said the patient inter-relationship plot comprising multiple feature plots of selected features, each of the feature plots on the perimeter showing the variation profile of a feature for each of the patient samples; and   a sample information panel adjacent said patient inter-relationship plot displaying patient sample information.   
     
     
         2 . A computer-implemented method of  claim 1 , wherein the patient inter-relationship plot comprises:
 a selected patient icon for a primary selected patient;   a patient feature value indicator on each of the feature plots for the selected patient; and   multiple display lines connecting the selected patient icon to each of the patient feature value indicators.   
     
     
         3 . A computer-implemented method of  claim 2 , further comprising:
 receiving an input from the user selecting a specific feature value indicator; and   displaying the value associated with the specific feature value indicator.   
     
     
         4 . A computer-implemented method of  claim 2 , wherein the patient inter-relationship plot further comprises:
 a sub-perimeter comprising multiple feature plots of selected features corresponding to the features plots on the perimeter, each of the feature plots on the sub-perimeter showing the variation profile of a feature for each of the patient samples at a different point in time from the feature plots on the perimeter;   a patient feature value indicator on each of the feature plots on the sub-parimeter for the selected patient,   wherein the multiple display lines further connect the selected patient icon to each of the patient feature value indicators at the sub perimeter.   
     
     
         5 . A computer-implemented method of  claim 2 , wherein the patient inter-relationship plot further comprises:
 a sub-perimeter, each comprising multiple additional feature plots of selected features, each of the feature plots on the sub-perimeter showing the variation profile of a feature for each of the patient samples;   a patient feature value indicator on each of the feature plots on the sub-parimeter(s) for the selected patient,   wherein the multiple display lines further connect the selected patient icon to each of the patient feature value indicators at the sub perimeter.   
     
     
         6 . A computer-implemented method of  claim 2 , wherein patient sample information in the sample information panel corresponding to the selected patient is highlighted. 
     
     
         7 . A computer-implemented method of  claim 1 , wherein the patient icons are grouped according to a subtype, and each group is indicated and labeled. 
     
     
         8 . A computer-implemented method of  claim 1 , further comprising receiving input from a user indicating cohort criteria for selecting patient samples to form the cohort of patient samples. 
     
     
         9 . A computer-implemented method of  claim 1 , further comprising receiving input from a user indicating which feature plots to display. 
     
     
         10 . A computer-implemented method of  claim 1 , further comprising receiving input from a user indicating the locations of the feature plots to display. 
     
     
         11 . A computer-implemented method of  claim 1 , further comprising:
 receiving input from a user a selecting a specific feature plot; and   displaying an expanded instance of the specifed feature plot with further information.   
     
     
         12 . A computer-implemented method of  claim 1 , wherein the feature plots grouped in segments along the perimeter according to feature groupings. 
     
     
         13 . A computer-implemented method of  claim 1 , further comprises receiving input from a user selecting at least two different patient icons wherein the patient inter-relationship plot comprises:
 a selected patient icon for each of the selected patients;   a patient feature value indicator on each of the feature plots for each of the selected patients; and   multiple display lines connecting each of the selected patient icons to each of the associated patient feature value indicators.   
     
     
         14 . A computer-implemented method of  claim 13 , wherein the feature value indicators and multiple display lines associated with each selected patient icon have different visual schema. 
     
     
         15 . A computer-implemented method of  claim 1 , wherein at least two patient inter-relationship values indicate a similarity distance between patients. 
     
     
         16 . A computer-implemented method of  claim 1 , wherein at least two patient inter-relationship values indicate a clustering of patients by subtype. 
     
     
         17 . A computer-implemented method of  claim 1 , further comprising:
 additional patient inter-relationship plots wherein the patient inter-relationship plots are displayed in 3-dimensions where each patient inter-relationship plot is a layer in the display, wherein the additionally patient inter-relationship plots are for different patients and/or cohorts of patient samples.   
     
     
         18 . A computer-implemented method of  claim 6 , further comprising:
 receiving a user selection selecting one of the patient inter-relationship plots; and   displaying only the selected patient inter-relationship plot.   
     
     
         19 . A computer-implemented method of  claim 1 , further comprising receiving input from a user indicating a switch to a tile view, wherein each of the feature plots are additionaly presented in a separate tile. 
     
     
         20 . A computer-implemented method of  claim 1 , further comprising:
 receiving input from a user selecting a plurality patient icons;   performing a statistical anlysis on the patient sample data for the selected patient icons; and   displaying a single combined patient icon on the patient inter-relationship plot using the results of the statistical analysis in place of the plurality of selected patient icons.   
     
     
         21 . A computer-implemented method of  claim 1 , further comprising:
 receiving input from a user indicating that the user is hovering over a specific patient icon; and   while the user indication is received displaying a patient feature value indicator on each of the feature plots for the specific patient icon and multiple display lines connecting the selected patient icon to each of the patient feature value indicators.